Replication data for: PosGNN: a graph neural network-based multimodal data fusion for indoor positioning in industrial non-line-of-sight scenarios

DOI

This dataset was created within the framework of the 5GSmartFact project (https://www.5gsmartfact.upc.edu/). It contains Ultra-Wideband (UWB) and Inertial Measurement Unit (IMU) datasets collected during a measurement campaign at ARENA2036, Germany. The dataset comprises two folders, namely, Training_dataset and Testing_dataset, for evaluating the Graph Neural Network-based sensor fusion framework.

Identifier
DOI https://doi.org/10.34810/DATA2963
Related Identifier IsSupplementTo https://doi.org/10.1109/OJVT.2025.3630970
Metadata Access https://dataverse.csuc.cat/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34810/DATA2963
Provenance
Creator Muthineni, Karthik ORCID logo; Artemenko, Alexander ORCID logo; Abode, Daniel ORCID logo; Vidal, Josep ORCID logo; Najar, Montse ORCID logo
Publisher CORA.Repositori de Dades de Recerca
Contributor Muthineni, Karthik; Universitat Politècnica de Catalunya; 160(RI)
Publication Year 2026
Funding Reference European Commission 956670
Rights CC0 1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Contact Muthineni, Karthik (Universitat Politècnica de Catalunya)
Representation
Resource Type Measurement and test data; Dataset
Format text/plain; text/tab-separated-values
Size 6745; 51605; 37416; 540710
Version 1.1
Discipline Other